Kemal Yaylali
11fb6b3d73
An end-to-end audit found the repo could not build, test or run as shipped. This fixes every finding, then adds a Cloud Run track so the demo costs about £1/month idle instead of ~£150. CI (red on its first run) - api: setuptools could not build the package (flat layout with app/ and alembic/) - web: missing @types/node; `vitest run` exited 1 with no test files - pipeline: the stub run needed a gitignored VCF, and no process had a stub block - ruff pinned, mypy configured, DB tests on real Postgres (pgserver locally, service in CI) ML serving (scores were meaningless) - the registered model now carries its own feature engineering and returns predict_proba, so serving sends raw columns and cannot drift from training - resolve by registry alias (stages are deprecated in MLflow 3) and record the real version; re-scoring upserts instead of failing on the unique constraint - ClinVar labels parsed from VEP's lowercase terms Pipeline - exact ref/alt recovered from a CHROM_POS_REF_ALT VCF ID; loading is idempotent - job status reaches running/failed/succeeded, so the UI stops polling dead jobs - DATABASE_URL travels in the environment or a Nextflow secret, never on a command line - VEP cache and plugins staged as inputs; the gcp profile runs tasks on Google Batch Deployment - the API serves /api (matching the ingress); the web app reads its API URL at runtime - migrations run in an init container under a Postgres advisory lock - terraform: custom VPC shared with Batch, private Cloud SQL, API enablement, Workload Identity bindings, Secret Manager, deletion protection - serverless track, now the default: Cloud Run services scaling to zero, a Cloud Run job for the Nextflow driver, and Neon or Cloud SQL behind one DATABASE_URL secret. GKE and Argo remain, behind -var deploy_kubernetes=true. See docs/cloud.md. Correctness and security - 409 on duplicate sample names, 422 on bad paging, natural chromosome ordering, wider VEP text columns, enum dropped on downgrade, the sample's assembly actually used - vcf_uri restricted to gs:// objects or files under the data root, blocking option injection - CORS restricted to configured origins; `make down` no longer deletes volumes Data - docs/data.md records the peer-reviewed, openly licensed sources (GIAB HG002, ClinVar, gnomAD) with citations and an honest evaluation plan; `make data` fetches a chr22 slice Verified: api 50 tests, ml 18, loader 16, web 12; ruff, mypy, svelte-check, terraform validate and both kustomize overlays clean.
38 lines
1.4 KiB
Bash
Executable File
38 lines
1.4 KiB
Bash
Executable File
#!/usr/bin/env bash
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# Fetch the public demo slice: a real GIAB genome and real ClinVar labels, chr22 only.
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# Provenance, licences and citations: docs/data.md
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set -euo pipefail
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OUT_DIR=${OUT_DIR:-data}
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CLINVAR_URL=${CLINVAR_URL:-https://ftp.ncbi.nlm.nih.gov/pub/clinvar/vcf_GRCh38/clinvar.vcf.gz}
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GIAB_URL=${GIAB_URL:-https://ftp-trace.ncbi.nlm.nih.gov/ReferenceSamples/giab/release/AshkenazimTrio/HG002_NA24385_son/NISTv4.2.1/GRCh38/HG002_GRCh38_1_22_v4.2.1_benchmark.vcf.gz}
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for tool in bcftools tabix; do
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command -v "$tool" >/dev/null || {
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echo "$tool is required (brew install bcftools, or apt install bcftools tabix)" >&2
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exit 1
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}
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done
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mkdir -p "$OUT_DIR"
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# Both sources are indexed, so bcftools streams one chromosome instead of downloading a whole
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# genome. ClinVar names contigs "22"; GIAB names them "chr22".
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echo "==> GIAB HG002 (NA24385) v4.2.1 benchmark, chr22 -> $OUT_DIR/example.vcf.gz"
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bcftools view -r chr22 "$GIAB_URL" -Oz -o "$OUT_DIR/example.vcf.gz"
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tabix -f -p vcf "$OUT_DIR/example.vcf.gz"
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echo "==> ClinVar GRCh38, chr22 -> $OUT_DIR/clinvar.chr22.vcf.gz"
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bcftools view -r 22 "$CLINVAR_URL" -Oz -o "$OUT_DIR/clinvar.chr22.vcf.gz"
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tabix -f -p vcf "$OUT_DIR/clinvar.chr22.vcf.gz"
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echo
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echo "Fetched:"
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ls -lh "$OUT_DIR/example.vcf.gz" "$OUT_DIR/clinvar.chr22.vcf.gz"
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cat <<'NEXT'
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Next:
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make pipeline VCF=data/example.vcf.gz # annotate the GIAB sample (needs a VEP cache)
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make annotate JOB=<job id> VCF=data/example.vcf.gz
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NEXT
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